Results 1 to 10 of about 22,442 (264)
Biomolecules, 2023 As the number of modalities in biomedical data continues to increase, the significance of multi-modal data becomes evident in capturing complex relationships between biological processes, thereby complementing disease classification. However, the current
Weidong Xie +4 more
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Optical Flow-Aware-Based Multi-Modal Fusion Network for Violence Detection [PDF]
Entropy, 2022 Violence detection aims to locate violent content in video frames. Improving the accuracy of violence detection is of great importance for security. However, the current methods do not make full use of the multi-modal vision and audio information, which ...
Yang Xiao +3 more
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MTMF-Grid: A multi-task multi-modal fusion model for operational forecasting and decision support in power grids. [PDF]
PLoS ONEPower grid strategic emerging business investment features multi-objective coupling and multi-source heterogeneous data. It requires simultaneous completion of regression and classification tasks, making traditional single-task or single-modal assessment
Dongyu Zhang +5 more
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Multi-modal Emotion Recognition Based on Dynamic Convolution and Residual Gating [PDF]
Jisuanji gongcheng, 2023 To prevent important information containing emotional cues from being obscured by irrelevant information in discourse and to achieve multi-modal information interaction, a multi-modal emotion recognition model based on dynamic convolution and residual ...
Yanxia GUO, Yong JIN, Hong TANG, Jinzhi PENG
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YOLO-Based Multi-Modal Weighted Fusion Pedestrian Detection Algorithm [PDF]
Jisuanji gongcheng, 2021 The performance of single-modal pedestrian detection algorithms based on visible images is limited in the cases of insufficient light at night, lack of information caused by target occlusion, and multi-scale targets. In order to improve the robustness of
SHI Zheng, MAO Li, SUN Jun
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Multi-Modal Named Entity Recognition Method Based on Multi-Task Learning [PDF]
Jisuanji gongcheng, 2023 With the aim of overcoming the ineffectiveness of traditional multi-modal Named Entity Recognition (NER)methods in integrating text and image modal information and distinguishing confusable entities, a multi-modal NER method based on multi-task learning ...
LI Xiaoteng, ZHANG Panpan, GOU Zhinan, GAO Kai
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Efficient Multi-Modal Fusion with Diversity Analysis [PDF]
Proceedings of the 29th ACM International Conference on Multimedia, 2021 Multi-modal machine learning has been a prominent multi-disciplinary research area since its success in complex real-world problems. Empirically, multi-branch fusion models tend to generate better results when there is a high diversity among each branch of the model.
Shuhui Qu, Yan Kang 0004, Janghwan Lee
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Multi-Modal Fusion by Meta-Initialization
CoRR, 2022 The first two authors contributed ...
Matthew Thomas Jackson +3 more
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CMBF: Cross-Modal-Based Fusion Recommendation Algorithm
Sensors, 2021 A recommendation system is often used to recommend items that may be of interest to users. One of the main challenges is that the scarcity of actual interaction data between users and items restricts the performance of recommendation systems.
Xi Chen +3 more
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Multi-Modal Domain Fusion for Multi-modal Aerial View Object Classification
CoRR, 2022 Object detection and classification using aerial images is a challenging task as the information regarding targets are not abundant. Synthetic Aperture Radar(SAR) images can be used for Automatic Target Recognition(ATR) systems as it can operate in all-weather conditions and in low light settings.
Sumanth Udupa +2 more
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